Introduction to Probability and Data with R
link Source: www.coursera.org
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assignment Level : Introductory
chat_bubble_outline Language : English
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Key Information

credit_card Free access
verified_user Fee-based Certificate
timer 80 hours in total

About the content

This course introduces you to the discipline of statistics as a science of understanding and analyzing data. You will learn how to effectively make use of data in the face of uncertainty: how to collect data, how to analyze data, and how to use data to make inferences and conclusions about real world phenomena.

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Syllabus

Week 1: Unit 1 - Introduction to data
  • Part 1 – Designing studies
  • Part 2 – Exploratory data analysis
  • Part 3 – Introduction to inference via simulation
Week 2: Unit 2 - Probability and distributions
  • Part 1 – Defining probability
  • Part 2 – Conditional probability
  • Part 3 – Normal distribution
  • Part 4 – Binomial distribution
Week 3: Unit 3 - Foundations for inference
  • Part 1 – Variability in estimates and the Central Limit Theorem
  • Part 2 – Confidence intervals
  • Part 3 – Hypothesis tests
Week 4: Finish up Unit 3 + Midterm
  • Part 4 – Inference for other estimators
  • Part 5 - Decision errors, significance, and confidence
Week 5: Unit 4 - Inference for numerical variables
  • Part 1 – t-inference
  • Part 2 – Power
  • Part 3 – Comparing three or more means (ANOVA)
  • Part 4 – Simulation based inference for means
Week 6: Unit 5 - Inference for categorical variables
  • Part 1 – Single proportion
  • Part 2 – Comparing two proportions
  • Part 3 – Inference for proportions via simulation
  • Part 4 – Comparing three or more proportions (Chi-square)
Week 7: Unit 6 - Introduction to linear regression
  • Part 1 – Relationship between two numerical variables
  • Part 2 – Linear regression with a single predictor
  • Part 3 – Outliers in linear regression
  • Part 4 – Inference for linear regression
Week 8: Unit 7 - Multiple linear regression
  • Part 1 – Regression with multiple predictors
  • Part 2 – Inference for multiple linear regression
  • Part 3 – Model selection
  • Part 4 – Model diagnostics
Week 9: Review / catch-up week
  • Bayesian vs. frequentist inference
Week 10: Final exam
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Instructors

  • Mine Çetinkaya-Rundel - Department of Statistical Science
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Content Designer

Duke University

Duke University is a private North American research university located in Durham, North Carolina. The university is named after the Duke dynasty. 

Although the university was not officially founded until 1924 (its roots go back to 1838). Frequently referred to as the "Harvard of the South", Duke is the most selective university in the American South. 

The university is a member of the Association of American Universities, an association which, since 1900, has brought together the elite research universities of North America.

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Platform

Coursera

Coursera is a digital company offering massive open online course founded by computer teachers Andrew Ng and Daphne Koller Stanford University, located in Mountain View, California. 

Coursera works with top universities and organizations to make some of their courses available online, and offers courses in many subjects, including: physics, engineering, humanities, medicine, biology, social sciences, mathematics, business, computer science, digital marketing, data science, and other subjects.

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Best Review

Am truely impress with content, Platform and animation this site provides to learners. Looking forward to enrich my data analysis skills

Published on September 16, 2020
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September 16, 2020
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Am truely impress with content, Platform and animation this site provides to learners. Looking forward to enrich my data analysis skills